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» The Dynamics of Multi-Agent Reinforcement Learning
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GECCO
2009
Springer
200views Optimization» more  GECCO 2009»
15 years 4 months ago
Apply ant colony optimization to Tetris
Tetris is a falling block game where the player’s objective is to arrange a sequence of different shaped tetrominoes smoothly in order to survive. In the intelligence games, ag...
Xingguo Chen, Hao Wang, Weiwei Wang, Yinghuan Shi,...
IROS
2006
IEEE
147views Robotics» more  IROS 2006»
15 years 3 months ago
A Hybrid Control Architecture for Autonomous Robotic Fish
— This paper presents a hybrid control architecture for autonomous robotic fishes which are able to swim and navigate in unknown or dynamically changing environments. It has a t...
Jindong Liu, Huosheng Hu, Dongbing Gu
ESANN
2008
14 years 11 months ago
Improvement in Game Agent Control Using State-Action Value Scaling
The aim of this paper is to enhance the performance of a reinforcement learning game agent controller, within a dynamic game environment, through the retention of learned informati...
Leo Galway, Darryl Charles, Michaela M. Black
ICRA
2009
IEEE
125views Robotics» more  ICRA 2009»
15 years 4 months ago
Learning motor primitives for robotics
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...
Jens Kober, Jan Peters
IJCAI
2003
14 years 11 months ago
An Integrated Multilevel Learning Approach to Multiagent Coalition Formation
In this paper we describe an integrated multilevel learning approach to multiagent coalition formation in a real-time environment. In our domain, agents negotiate to form teams to...
Leen-Kiat Soh, Xin Li